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Created on Wednesday, 04 June 2014 12:12

Last Updated on Wednesday, 04 June 2014 12:25

Written by Ami Ronnberg

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The COGS project was initiated with the aim of identifying genetic determinates of breast, ovarian and prostate cancer. Furthermore, we wanted to identify the lifestyle factors that influence the risk of these cancers and explore possible interaction between inheritance and lifestyle factors. We also wanted to identify the genetics influence on type of tumour and prognosis of the diseases.

The generated information could be used for stratifying individuals in to risk of cancer thus enabling more efficient prevention and screening. Finally, we investigated the challenges using risk based strategies in prevention and screening and what ethical, legal and social implications these new approaches will have.

COGS generated the largest data set ever seen in cancer research including 239,832 individuals from 167 research groups from all over the world. We created our own costume made genotyping array, iCOGS, including 211,155 single nucleotide polymorphisms (SNPs). This was done through a lengthy and rigorous procedure where we used a combination of existing knowledge and previously genotyped datasets.

In all, 104 papers have been published based on COGS data. The main finding is the identification of new susceptibility markers for risk of breast, ovarian and prostate cancer. Before COGS started there were 73 markers for risk of these cancers (Table 1). Through COGS an additional 154 SNPs have been identified which means that COGS has contributed 68% of the currently known SNPs that influence the risk of breast, ovarian and prostate cancer.

Table 1. Number of established SNPs pre- and post the iCOGS analyses.

Pre-iCOGS1

iCOGS, phase I2

iCOGS, phase II3

TOTAL

Breast cancer

27

45

47

119

Prostate cancer

42

26

22

90

Ovarian cancer

4

8

6

18

Total

73

79

75

227

The major implication of the COGS results are that we are far better today than 5 years ago when it comes to predicting who will later in life be diagnosed with three major types of cancer. We have shown that this knowledge could be used risk stratification that in turn could improve our abilities to prevent cancer and/or detect the disease in an early stage.